State Water Resources Research Institute Program
Project ID: 2008DC93B
Title: Development of Web-based Rainfall Statistical Analyisis Tool for Urban Stormwater Management Analsis
Project Type: Research
Start Date: 3/01/2008
End Date: 2/28/2009
Congressional District: District of Columbia
Focus Categories: Management and Planning, Non Point Pollution
Keywords: Analytical Models, Urban Stormwater Models, Statistical analysis, storm event analysis
Principal Investigator: Behera, Pradeep K.
Federal Funds: $ 8,200
Non-Federal Matching Funds: $ 10,828
Abstract: The analysis of urban stormwater pollution is a primary step in developing cost-effective solutions for wet-weather flow problems. Often the solutions are proposed based on limited monitoring and modeling efforts due to their exorbitant cost. Continuous simulation models have been used to analyze the existing watershed and stormwater pollution condition and to develop alternative solutions. The example of continuous simulation model includes EPA SWMM. As these models are resource intensive, often development of watershed-wide simulation models is avoided during planning-level analysis. On the other hand analytical probabilistic models are computational efficient compared to continuous simulation models and can be easily used to develop the watershed-wide model.
Especially, for the District of Columbia sewer system, analytical models can be easily applied to analyze the existing water pollution problem and to develop alternate solutions. The primary input to the analytical stormwater model is statistical parameters of the long-term rainfall record. The federal agencies such as NOAA and NCDC provide the meteorological data which are typically used by the continuous simulation models. The rainfall records are generally pre-processed for the use in the stormwater models. However, analytical models use the same long-term rainfall records in a different manner. The long-term rainfall records are statistically analyzed and fitted with several probability distribution functions. The parameters of best fitted probability distribution functions for the rainfall characteristics such as storm event volume, event duration, event intensity and inter-event time, are used in the analytical models in lieu of continuous record.
The proposed web based statistical tool will provide the user much functionality. They include (i) extraction of rainfall records from the NOAA and NCDC sites; (ii) preprocessing of data for statistical analysis; (iii) fitting of probability distribution functions and estimation of their parameters.
Progress/Completion Report, PDF